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What influences the substitution of ride-sourcing for public transit and taxi services in Toronto? An exploratory structural equation model-based study

公共交通 TRIPS体系结构 人气 模式选择 结构方程建模 业务 营销 运输工程 描述性统计 工程类 计算机科学 心理学 数学 社会心理学 统计 机器学习
作者
Patrick Loa,Sk. Md. Mashrur,Khandker Nurul Habib
出处
期刊:International Journal of Sustainable Transportation [Informa]
卷期号:17 (1): 15-28 被引量:7
标识
DOI:10.1080/15568318.2021.1978018
摘要

The continued growth and utilization of ride-sourcing services have reshaped traditional perceptions of urban mobility. As the popularity of this relatively novel mode of travel has continued to grow, there has been a greater focus on the effect that the adoption and use of ride-sourcing have on the utilization of more traditional modes of transportation. With a few notable exceptions, prior studies on the topic often rely on descriptive statistics to understand the modes that are replaced by ride-sourcing for specific trips. This study utilizes structural equation models to investigate the factors influencing the decision to choose public transit and taxi as their so-called substitute alternative mode for a recent ride-sourcing trip, using data from a web-based survey of Toronto residents. The results indicate that socio-economic and trip-related attributes influence the selection of the substitute alternative mode, and to a lesser extent, attitudes toward ride-sourcing services. In particular, students, persons from lower-income households, and transit pass owners were found to be more likely to substitute ride-sourcing for public transit, while older respondents and persons from wealthier households were more likely to select taxi instead. The study outcomes shed light on the types of transit trips that are more likely to be replaced in favor of ride-sourcing services and the attributes of individuals who are more likely to make this replacement. This information can inform policies that aim to reduce the substitution of ride-sourcing for public transit, which can worsen both congestion and emissions.

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